Determination of the downwelling diffuse attenuation coefficient of lakewater with the sentinel-3A OLCI

The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400-1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (Kd(490)) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available Kd(490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R2) = 0.81, root-mean-square error (RMSE) = 0.99m-1and mean absolute percentage error (MAPE) = 19.55%) and validation accuracy (N = 14, R2= 0.83, RMSE = 1.06 m-1and MAPE = 27.30%), making it more suitable for turbid inland waters; (2) A comparison of the OLCI Kd(490) product and a similar Moderate Resolution Imaging Spectroradiometer (MODIS) product reveals a high consistency between the OLCI and MODIS products in terms of the spatial distribution of Kd(490). However, the OLCI product has a smoother spatial distribution and finer textural characteristics than the MODIS product and contains notably higher-quality data; (3) The Kd(490) values for Lake Taihu exhibit notable spatial and temporal variations. Kd(490) is higher in seasons with relatively high wind speeds and in open waters that are prone to wind- and wave-induced sediment resuspension. Finally, the Sentinel-3A-OLCI has a higher spatial resolution and is equipped with a relatively wide dynamic range of spectral bands suitable for inland waters. The Sentinel-3B satellite will be launched soon and, together with the Sentinel-3A satellite, will form a two-satellite network with the ability to make observations twice every three days. This satellite network will have a wider range of application and play an important role in the monitoring of inland waters with complex optical properties

A semi-analytical algorithm for deriving the particle size distribution slope of turbid inland water based on OLCI data: A case study in Lake Hongze

The particle size distribution (PSD) slope (ξ) can indicate the predominant particle size, material composition, and inherent optical properties (IOPs) of inland waters. However, few semi-analytical methods have been proposed for deriving ξ from the surface remote sensing reflectance due to the variable optical state of inland waters. A semi-analytical algorithm was developed for inland waters having a wide range of turbidity and ξ in this study. Application of the proposed model to Ocean and Land Color Instrument (OLCI) imagery of the water body resulted in several important observations: (1) the proposed algorithm (754 nm and 779 nm combination) was capable of retrieving ξ with R2 being 0.72 (p < 0.01, n = 60), and MAPE and RMSE being 4.37% and 0.22 (n = 30) respectively; (2) the ξ in HZL was lower in summer than other seasons during the period considered, this variation was driven by the phenological cycle of algae and the runoff caused by rainfall; (3) the band optimization proposed in this study is important for calculating the particle backscattering slope (η) and deriving ξ because it is feasible for both algae dominant and sediment governed turbid inland lakes. These observations help improve our understanding of the relationship between IOPs and ξ, which are affected by different bio-optic processes and algal phenology in the lake environment

A semi-analytical model for estimating total suspended matter in highly turbid waters

Total suspended matter (TSM) is related to water quality. High TSM concentrations limit underwater light availability, thus affecting the primary productivity of aquatic ecosystems. Accurate estimation of TSM concentrations in various waters with remote sensing technology is particularly challenging, as the concentrations and optical properties vary greatly among different waters. In this research, a semi-analytical model was established for Hangzhou Bay and Lake Taihu for estimating TSM concentration. The model construction proceeded in two steps. 1) Two indices of the model were calculated by deriving absorption and backscattering coefficients of suspended matter (ap(&#x03BB;) and bbp(&#x03BB;)) from the reflectance signal using a semi-analytical method. 2) The two indices were then weighted to derive TSM. The performance of the proposed model was tested using in situ reflectance and Geostationary Ocean Color Imager (GOCI) data. The derived TSM based on in situ reflectance and GOCI images both corresponded well with the in situ TSM with low mean relative error (32%, 41%), root mean square error (20.1 mg/L, 43.1 mg/L), and normalized root mean square error (33%, 55%). The model was further used for the slightly turbid Xin&#x2019;anjiang Reservoir to demonstrate its applicability to derive ap(&#x03BB;) and bbp(&#x03BB;) in other water types. The results indicated that the form Rrs &#x2212;1(&#x03BB;1) &#x2212; Rrs &#x2212;1(&#x03BB;2) could minimize the effect of CDOM absorption in deriving ap(&#x03BB;) from the total absorption. The model exploited the different relationships between TSM concentration and multiband reflectance, thus improving the performance and application range in deriving TSM

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China\u27s three largest freshwater lakes

Inherent optical properties (IOPs) play an important role in underwater light field, and are difficult to estimate accurately using satellite data in optically complex waters. To study water quality in appropriate temporal and spatial scales, it is necessary to develop methods to obtain IOPs form space-based observation with quantified uncertainties. Field-measured IOP data (N = 405) were collected from 17 surveys between 2011 and 2017 in the three major largest freshwater lakes of China (Lake Chaohu, Lake Taihu, and Lake Hongze) in the lower reaches of the Yangtze River and Huai River (LYHR). Here we provide a case-study on how to use in-situ observation of IOPs to devise an improved algorithm for retrieval of IOPs. We then apply this algorithm to observation with Sentinel-3A OLCI (Ocean and Land Colour Instrument, corrected with our improved AC scheme), and use in-situ data to show that the algorithm performs better than the standard OLCI IOP product. We use the satellite derived products to study the spatial and seasonal distributions of IOPs and concentrations of optically active constituents in these three lakes, including chlorophyll-a (Chla) and suspended particulate matter (SPM), using all cloud-free OLCI images (115 scenes) over the lakes in the LYHR basin in 2017. Our study provides a strategy for using local and remote observations to obtain important water quality parameters necessary to manage resources such as reservoirs, lakes and coastal waters

Algorithm to derive inherent optical properties from remote sensing reflectance in turbid and eutrophic lakes

Inherent optical properties play an important role in understanding the biogeochemical processes of lakes by providing proxies for a variety of biogeochemical quantities, including phytoplankton pigments. However, to date, it has been difficult to accurately derive the absorption coefficient of phytoplankton [aph(λ)] in turbid and eutrophic waters from remote sensing. A large dataset of remote sensing of reflectance [ Rrs (λ)] and absorption coefficients was measured for samples collected from lakes in the middle and lower reaches of the Yangtze River and Huai River basin (MLYHR), China. In the process of scattering correction of spectrophotometric measurements, the particulate absorption coefficients [ap(λ)] were first assumed to have no absorption in the near-infrared (NIR) wavelength. This assumption was corrected by estimating the particulate absorption coefficients at 750 nm [ap(750)] from the concentrations of chlorophyll-a (Chla) and suspended particulate matter, which was added to the ap(λ) as a baseline. The resulting mean spectral mass-specific absorption coefficient of the nonalgal particles (NAPs) was consistent with previous work. A novel iterative IOP inversion model was then designed to retrieve the total nonwater absorption coefficients [anw(λ)] and backscattering coefficients of particulates [bbp(λ)], aph(λ), and adg (λ) [absorption coefficients of NAP and colored dissolved organic matter (CDOM)] from Rrs (λ) in turbid inland lakes. The proposed algorithm performed better than previously published models in deriving anw(λ) and bbp(λ) in this region. The proposed algorithm performed well in estimating the aph(λ) for wavelengths \u3e 500 nm for the calibration dataset [N = 285, unbiased absolute percentage difference (UAPD) = 55.22%, root mean square error (RMSE) = 0.44 m−1] and for the validation dataset (N = 57, UAPD = 56.17%, RMSE = 0.71 m−1). This algorithm was then applied to Sentinel-3A Ocean and Land Color Instrument (OLCI) satellite data, and was validated with field data. This study provides an example of how to use local data to devise an algorithm to obtain IOPs, and in particular, a ph (λ), using satellite Rr s (λ) data in turbid inland waters

Cyanobacteria in Inland Waters: Remote Sensing

Remote sensing plays important roles in managing harmful cyanobacterial blooms. Remote sensing algorithms for monitoring cyanobacterial blooms are grouped into empirical, semi-empirical, and semi-analytical methods. In this chapter, 12 of these methods were selected to be reviewed for their performances when applied to in situ measured field reflectance spectra and airborne or satellite sensor collected image spectra. Five empirical PC algorithms based on either band ratio or baseline calculation showed data-dependent performances, empirical band ratios and the baseline can be used to build semi-empirical models such as double three band baseline (DTBB) and four band baseline model (FBBM) showing stronger performance than the three band model (TBM), and the DTBB even performing stronger than the nested band ratio (NBR). As far as three semi-analytical models concern, the NBR and EIIMIW consistently performed well compared to the QAA pc , but care or recalibration should be practiced for applying both EIIMIW and NBR given caring inherent optical property of non-phycocyanin (PC) constituent in the water column. Although neither DTBB nor FBM cannot be evaluated with satellite MEdium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Color Instrument (OLCI) images, they should be tested in future with hyperspectral satellite images acquired by PRISMA, EnMAP, and HyspIRI

Fluid mixing processes in enclosed shallow water flows and applications

PhD ThesisThis work develops a numerical modelling tool to investigate and better understand the fluid mixing processes in enclosed or semi-closed shallow water flows. The integrated fluid mixing modelling framework consists of two components, i.e. a shallow flow model for predicting hydrodynamics and a particle-tracking model for calculating the trajectories of passive particles released in the water bodies. The well-defined analysis method in dynamical system theory, Finite Time Lyapunov Exponent (FTLE), is used to extract the Lagrangian Coherent Structures (LCSs) to provide insight of the nonlinear particle dynamics in the time-dependant environmental shallow water flows under consideration. The fluid mixing modelling and analysis framework is firstly used to study the mixing properties of an oscillating environmental flow driven by two inflows and one outflow in an idealised shallow basin. The Eulerian velocity field of the flow is first predicted using the shallow flow model, which is then used by the particle-tracking model to calculate the particle trajectories and describe the transport and mixing properties of the inflows/outflow driven shallow water flow. The particle dynamics is found to be controlled by a dimensionless parameter and fluid mixing changes from regular to chaotic when the magnitude of the parameter increases. The integrated numerical modelling framework is then applied to reproduce the wind-driven flow hydrodynamics and investigate the corresponding fluid mixing in Taihu, one of the largest fresh water lakes in China, for continuous 12 months. The predicted flow field, which is used to drive the particle dynamics, compares favourably with the field measurements. The transport and mixing properties of the lake are analysed by calculating the FTLE and identifying the LCSs, clearly revealing the stagnant and well-mixing zones of the water body. The understanding of the underlying fluid mixing mechanism of the lake is also improved. Through successful application to one idealised and one realistic case studies, the potential of the current integrated numerical modelling framework is confirmed for analysing fluid mixing in (semi-)enclosed water bodies.‘The Henry Lester Trust Limited’ and ‘The Great Britain-China Educational Trust’, for their financial supporting in the third and fourth year of my progra

Remote sensing and bio-geo-optical properties of turbid, productive inland waters: a case study of Lake Balaton

Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters

A transferable bio-optical model for quantification of inland water caynobacterial pigments

Indiana University-Purdue University Indianapolis (IUPUI)Cyanobacterial blooms are currently one of the most important issues faced by environmental agencies, water authorities and public health organizations. Remote sensing provides an advanced approach to monitor cyanobacteria by detecting and quantifying chlorophyll-a (Chl-a) and phycocaynin (PC). In this thesis, an analytical bio-optical model, more typically applied to ocean waters, was modified to accommodate the complexity of inland waters. The newly developed models work well to estimate inherent optical properties, including absorption and backscattering coefficients, in eight different study sites distributed around the globe. Based on derived absorption coefficients, Chl-a and PC concentrations were accurately retrieved for data sets collected annually from 2006 to 2010, and the estimation accuracy exceeded that of currently used algorithms. An important advantage of the model is that low concentrations of Chl-a and PC can be predicted more accurately, enabling early warning of cyanobacterial blooms. In addition, the results also indicated good spatial and temporal transferability of the algorithms, since no specific calibration procedures were required for data sets collected in a different sites and seasons. The compatibility of the newly developed algorithm with MERIS spectra provides the possibility for routine surveillance of cyanobacterial growth in inland waters

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Several semi-analytical algorithms have been developed to estimate the chlorophyll-a (Chl-a) and phycocyanin (PC) concentrations in inland waters. This study aimed at identifying the influence of algorithm parameters on the output variables and searching optimal parameter values. The optimal parameters of seven semi-analytical algorithms were applied to estimate the Chl-a and PC concentrations. The absorption coefficient measurements were coupled with pigment measurements to calibrate the algorithm parameters. For sensitivity analysis, the elementary effect test was conducted to analyze the influence of the algorithm parameters. The sensitivity analysis results showed that the parameters in the Y function and specific absorption coefficient were the most sensitive parameters. Then, the parameters were optimized via a single-objective optimization that involved one objective function being minimized and a multi-objective optimization that contained more than one objective function. The single-objective optimization led to substantial errors in absorption coefficients. In contrast, the multi-objective optimization improved the algorithm performance with respect to both the absorption coefficient estimates and pigment concentration estimates. The optimized parameters of the absorption coefficient reflected the high-particulate content in waters of the Baekje reservoir using an infrared backscattering wavelength and relatively high value of Y. Moreover, the results indicate the value of measuring the site-specific absorption if site-specific optimization of semi-analyical algorithm parameters was envisioned